The normal mechanisms of pregnancy-induced liver growth are not maintained in mice lacking the bile acid sensor Fxr
Bibliographic record
Abstract
Rodents undergo gestational hepatomegaly to meet the increased metabolic demands on the maternal liver during pregnancy. This is an important physiological process, but the mechanisms and signals driving pregnancy-induced liver growth are not known. Here, we show that liver growth during pregnancy precedes maternal body weight gain, is proportional to fetal number, and is a result of hepatocyte hypertrophy associated with cell-cycle progression, polyploidy, and altered expression of cell-cycle regulators p53, Cyclin-D1, and p27. Because circulating reproductive hormones and bile acids are raised in normal pregnant women and can cause liver growth in rodents, these compounds are candidates for the signal driving gestational liver enlargement in rodents. Administration of pregnancy levels of reproductive hormones was not sufficient to cause liver growth, but mouse pregnancy was associated with increased serum bile acid levels. It is known that the bile acid sensor Fxr is required for normal recovery from partial hepatectomy, and we demonstrate that Fxr(-/-) mice undergo gestational liver growth by adaptive hepatocyte hyperplasia. This is the first identification of any component that is required to maintain the normal mechanisms of gestational hepatomegaly and also implicates Fxr in a physiologically normal process that involves control of the hepatocyte cell cycle. Understanding pregnancy-induced hepatocyte hypertrophy in mice could suggest mechanisms for safely increasing functional liver capacity in women during increased metabolic demand.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".